OpenAISan Francisco, CAOptimizes large AI models for high-volume, low-latency production and research environments. Collaborates with researchers and engineers on inference stack performance, requiring 5+ years experience with PyTorch, GPUs, CUDA, and distributed systems.
Improve agentic model capabilities, reliability, and product fit for power users and API developers through evals, training data, and post-training interventions.
Build and maintain infrastructure for large-scale RL training runs of frontier OpenAI models. Debug across training, inference, and distributed systems while supporting research integrations.
Hands-on senior software engineer focused on maintaining and improving ML training infrastructure, debugging training systems, and unblocking researchers on the robotics team.
Models inference performance across application, model, and fleet layers using microbenchmarks to build cost-to-serve estimates. Analyzes workloads end-to-end, enhances bottleneck detection tools, and collaborates on optimizations for latency, throughput, and cost.
Designs and scales distributed data infrastructure for large-scale multimodal AI training and evaluation. Collaborates with researchers to build reliable, high-performance systems in a fast-paced environment.